1. Field of the Invention
This invention relates to broadcast television and more specifically to the dynamic scheduling and broadcast of quasi on-demand programming.
2. Description of the Related Art
Television programming is broadcast over analog broadcast channels, cable services and satellite networks. Satellite service providers such as DIRECTV® and EchoStar Communications Corp. (Dish Network™) provide a wide variety of customer-based programming including regularly scheduled programming and pay-per-view (PPV). Satellite service providers would like to provide their customers with “On-Demand” programming in which a customer could view a Program Offer, select a program and have it downloaded to his or her television in virtually real-time. Unfortunately this is not presently viable due to channel constraints and economic considerations. Instead service providers are offering quasi On-Demand programming in which programs are broadcast to customers at unpublished times and downloaded to their digital video recorder (DVR) for playback at a later time. How the programs are selected and when they are broadcast depends on the service.
DIRECTV® and STARZ® jointly offer a “STARZ Subscription On-Demand” service freely to customers who are customers to both DIRECTV's DVR service and the STARZ service. STARZ selects a number of movies from its broadcast schedule that are automatically delivered by the DIRECTV network to qualifying customers. The movies are delivered overnight on random days during, for example, a two week period. The customer has no input in selecting what movies are sent or when they are sent. Furthermore until the customer checks his or her “inbox” the customer has no idea what movies will be sent or when. The service is provided to encourage customers to use the STARZ subscription services.
U.S. Pat. No. 5,790,935 describes a system for delivering virtual on-demand information over a digital transport system such as a satellite network by offloading a portion of the system's peak bandwidth requirements to the local customers. A collaborative filtering system synthesizes the preferences of all the customers and then predicts those items that each customer might like, and therefore request. Each customer is provided with a local storage device for storing, during off-peak hours, those items recommended by the collaborative filtering system. As a result, only a relatively few customer requests must be serviced directly from the central distribution system.